IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v462y2016icp321-329.html
   My bibliography  Save this article

Response of autaptic Hodgkin–Huxley neuron with noise to subthreshold sinusoidal signals

Author

Listed:
  • Wang, Hengtong
  • Chen, Yong

Abstract

In this work, we investigated the response of a stochastic Hodgkin–Huxley (HH) neuron with an autapse to subthreshold sinusoidal signals. It is found that the autapse not only adjusts the stochastic responses, but also improves the detection of subthreshold signals. In the case of weak noise, the autapse facilitates the response of neuron to the subthreshold sinusoidal signals with a small parameter region in tdelay-ω space. The increased noise intensity enlarges this parameter region and increases the corresponding response frequency in such range. As the autaptic intensity increases, however, this parameter region shrunks. We also observed that there is an optimal range of the delay time of autapse, within which the stochastic HH neuron fires action potentials with high frequency. The corresponding response spike train for the optimal delay time is nearly a regular sequence with the interspike intervals approximated to the delay time. The current results reveal a novel resonance phenomenon facilitated by autapse, named autaptic delay-induced coherence resonance.

Suggested Citation

  • Wang, Hengtong & Chen, Yong, 2016. "Response of autaptic Hodgkin–Huxley neuron with noise to subthreshold sinusoidal signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 321-329.
  • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:321-329
    DOI: 10.1016/j.physa.2016.06.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116302874
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2016.06.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yilmaz, Ergin & Uzuntarla, Muhammet & Ozer, Mahmut & Perc, Matjaž, 2013. "Stochastic resonance in hybrid scale-free neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5735-5741.
    2. Yilmaz, Ergin & Baysal, Veli & Ozer, Mahmut & Perc, Matjaž, 2016. "Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 538-546.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Uzun, Rukiye & Yilmaz, Ergin & Ozer, Mahmut, 2017. "Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 386-396.
    2. Ni Zhang & Dongxi Li & Yanya Xing, 2021. "Autapse-induced multiple inverse stochastic resonance in a neural system," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(1), pages 1-11, January.
    3. Xiao, Fangli & Fu, Ziying & Jia, Ya & Yang, Lijian, 2023. "Resonance effects in neuronal-astrocyte model with ion channel blockage," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    4. Baysal, Veli & Calim, Ali, 2023. "Stochastic resonance in a single autapse–coupled neuron," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    5. Yu, Haitao & Galán, Roberto F. & Wang, Jiang & Cao, Yibin & Liu, Jing, 2017. "Stochastic resonance, coherence resonance, and spike timing reliability of Hodgkin–Huxley neurons with ion-channel noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 263-275.
    6. Uzun, Rukiye, 2017. "Influences of autapse and channel blockage on multiple coherence resonance in a single neuron," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 203-210.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Ying & Jia, Ya & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Synchronization between neurons coupled by memristor," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 435-442.
    2. Mostaghimi, Soudeh & Nazarimehr, Fahimeh & Jafari, Sajad & Ma, Jun, 2019. "Chemical and electrical synapse-modulated dynamical properties of coupled neurons under magnetic flow," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 42-56.
    3. Yu, Haitao & Galán, Roberto F. & Wang, Jiang & Cao, Yibin & Liu, Jing, 2017. "Stochastic resonance, coherence resonance, and spike timing reliability of Hodgkin–Huxley neurons with ion-channel noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 263-275.
    4. Aghababaei, Sajedeh & Balaraman, Sundarambal & Rajagopal, Karthikeyan & Parastesh, Fatemeh & Panahi, Shirin & Jafari, Sajad, 2021. "Effects of autapse on the chimera state in a Hindmarsh-Rose neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    5. Guo, Xinmeng & Yu, Haitao & Wang, Jiang & Liu, Jing & Cao, Yibin & Deng, Bin, 2017. "Local excitation–inhibition ratio for synfire chain propagation in feed-forward neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 308-316.
    6. Ni Zhang & Dongxi Li & Yanya Xing, 2021. "Autapse-induced multiple inverse stochastic resonance in a neural system," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(1), pages 1-11, January.
    7. Xie, Huijuan & Gong, Yubing & Wang, Baoying, 2018. "Spike-timing-dependent plasticity optimized coherence resonance and synchronization transitions by autaptic delay in adaptive scale-free neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 1-7.
    8. Qin, Huixin & Wang, Chunni & Cai, Ning & An, Xinlei & Alzahrani, Faris, 2018. "Field coupling-induced pattern formation in two-layer neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 141-152.
    9. Erkaymaz, Okan & Ozer, Mahmut & Perc, Matjaž, 2017. "Performance of small-world feedforward neural networks for the diagnosis of diabetes," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 22-28.
    10. Peng, Lu & Tang, Jun & Ma, Jun & Luo, Jinming, 2022. "The influence of autapse on synchronous firing in small-world neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    11. Yu, Dong & Wu, Yong & Yang, Lijian & Zhao, Yunjie & Jia, Ya, 2023. "Effect of topology on delay-induced multiple resonances in locally driven systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Chunni Wang & Shengli Guo & Ying Xu & Jun Ma & Jun Tang & Faris Alzahrani & Aatef Hobiny, 2017. "Formation of Autapse Connected to Neuron and Its Biological Function," Complexity, Hindawi, vol. 2017, pages 1-9, February.
    13. Erkaymaz, Okan & Ozer, Mahmut, 2016. "Impact of small-world network topology on the conventional artificial neural network for the diagnosis of diabetes," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 178-185.
    14. Li, Fan, 2020. "Effect of field coupling on the wave propagation in the neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    15. Wu, Fuqiang & Wang, Ya & Ma, Jun & Jin, Wuyin & Hobiny, Aatef, 2018. "Multi-channels coupling-induced pattern transition in a tri-layer neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 54-68.
    16. Yu, Haitao & Guo, Xinmeng & Wang, Jiang & Deng, Bin & Wei, Xile, 2015. "Spike coherence and synchronization on Newman–Watts small-world neuronal networks modulated by spike-timing-dependent plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 307-317.
    17. Ge, Mengyan & Jia, Ya & Xu, Ying & Lu, Lulu & Wang, Huiwen & Zhao, Yunjie, 2019. "Wave propagation and synchronization induced by chemical autapse in chain Hindmarsh–Rose neural network," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 136-145.
    18. Yao, Chenggui & Ma, Jun & He, Zhiwei & Qian, Yu & Liu, Liping, 2019. "Transmission and detection of biharmonic envelope signal in a feed-forward multilayer neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 797-806.
    19. Uzun, Rukiye & Yilmaz, Ergin & Ozer, Mahmut, 2017. "Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 386-396.
    20. Qu, Lianghui & Du, Lin & Cao, Zilu & Hu, Haiwei & Deng, Zichen, 2021. "Pattern transition of neuronal networks induced by chemical autapses with random distribution," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:321-329. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.